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Testing for and estimating structural breaks and other nonlinearities in a dynamic monetary sector

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  • Ericsson Neil R.

    (Principal Economist, Division of International Finance, Board of Governors of the Federal Reserve System, Stop K1-02, 2000 C Street, N.W., Washington, DC 20551, USA)

Abstract

Milton Friedman and Anna Schwartz constructed an important macroeconomic dataset for the United Kingdom that spans 1878–1970. Numerous authors have modeled the demand for broad money on that dataset. Model selection is central to assessing the merits of the resulting empirical models, so the current paper re-evaluates that issue with computer-automated model selection. Some models are robust to the model selection path, as characterized through variations in target size, pre-search testing, fixity of regressors, impulse indicator saturation, representation of the general model, and choice of dependent variable. Model improvement is also feasible, with historically interpretable nonlinearities and structural breaks.

Suggested Citation

  • Ericsson Neil R., 2016. "Testing for and estimating structural breaks and other nonlinearities in a dynamic monetary sector," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(4), pages 377-398, September.
  • Handle: RePEc:bpj:sndecm:v:20:y:2016:i:4:p:377-398:n:6
    DOI: 10.1515/snde-2015-0104
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    References listed on IDEAS

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    1. Merton H. Miller & Daniel Orr, 1966. "A Model of the Demand for Money by Firms," The Quarterly Journal of Economics, Oxford University Press, vol. 80(3), pages 413-435.
    2. Marczak, Martyna & Proietti, Tommaso, 2016. "Outlier detection in structural time series models: The indicator saturation approach," International Journal of Forecasting, Elsevier, vol. 32(1), pages 180-202.
    3. Hendry, David F. & Johansen, Søren, 2015. "Model Discovery And Trygve Haavelmo’S Legacy," Econometric Theory, Cambridge University Press, vol. 31(1), pages 93-114, February.
    4. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
    5. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry & Felix Pretis, 2015. "Detecting Location Shifts during Model Selection by Step-Indicator Saturation," Econometrics, MDPI, Open Access Journal, vol. 3(2), pages 1-25, April.
    6. Teodosio Perez‐Amaral & Giampiero M. Gallo & Halbert White, 2003. "A Flexible Tool for Model Building: the Relevant Transformation of the Inputs Network Approach (RETINA)," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 65(s1), pages 821-838, December.
    7. Castle, Jennifer L. & Doornik, Jurgen A. & Hendry, David F., 2012. "Model selection when there are multiple breaks," Journal of Econometrics, Elsevier, vol. 169(2), pages 239-246.
    8. Milton Friedman & Anna Jacobson Schwartz, 1970. "Monetary Statistics of the United States: Estimates, Sources, Methods," NBER Books, National Bureau of Economic Research, Inc, number frie70-1, September.
    9. Jennifer L. Castle & Xiaochuan Qin & W. Robert Reed, 2013. "Using Model Selection Algorithms To Obtain Reliable Coefficient Estimates," Journal of Economic Surveys, Wiley Blackwell, vol. 27(2), pages 269-296, April.
    10. Carlos Santos & David Hendry & Soren Johansen, 2008. "Automatic selection of indicators in a fully saturated regression," Computational Statistics, Springer, vol. 23(2), pages 317-335, April.
    11. Godfrey, Leslie G, 1978. "Testing for Higher Order Serial Correlation in Regression Equations When the Regressors Include Lagged Dependent Variables," Econometrica, Econometric Society, vol. 46(6), pages 1303-1310, November.
    12. Hendry, David F., 1995. "Dynamic Econometrics," OUP Catalogue, Oxford University Press, number 9780198283164.
    13. Cochrane, John H, 1989. "The Sensitivity of Tests of the Intertemporal Allocation of Consumption to Near-Rational Alternatives," American Economic Review, American Economic Association, vol. 79(3), pages 319-337, June.
    14. Clements,Michael & Hendry,David, 1998. "Forecasting Economic Time Series," Cambridge Books, Cambridge University Press, number 9780521634809, August.
    15. Jurgen A. Doornik & Henrik Hansen, 2008. "An Omnibus Test for Univariate and Multivariate Normality," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(s1), pages 927-939, December.
    16. Milton Friedman & Anna Jacobson Schwartz, 1970. "Introduction to "Monetary Statistics of the United States: Estimates, Sources, Methods"," NBER Chapters, in: Monetary Statistics of the United States: Estimates, Sources, Methods, pages 1-85, National Bureau of Economic Research, Inc.
    17. Gregor W. Smith, 1986. "A Dynamic Baumol-Tobin Model of Money Demand," Review of Economic Studies, Oxford University Press, vol. 53(3), pages 465-469.
    18. David Hendry & Carlos Santos, 2010. "An Automatic Test of Super Exogeneity," Economics Series Working Papers 476, University of Oxford, Department of Economics.
    19. Felix Pretis & Michael Mann & Robert Kaufmann, 2015. "Testing competing models of the temperature hiatus: assessing the effects of conditioning variables and temporal uncertainties through sample-wide break detection," Climatic Change, Springer, vol. 131(4), pages 705-718, August.
    20. Campos, Julia & Ericsson, Neil R. & Hendry, David F., 1990. "An analogue model of phase-averaging procedures," Journal of Econometrics, Elsevier, vol. 43(3), pages 275-292, March.
    21. Milton Friedman & Anna J. Schwartz, 1963. "A Monetary History of the United States, 1867–1960," NBER Books, National Bureau of Economic Research, Inc, number frie63-1, September.
    22. Castle, Jennifer L. & Hendry, David F., 2010. "A low-dimension portmanteau test for non-linearity," Journal of Econometrics, Elsevier, vol. 158(2), pages 231-245, October.
    23. Timo Teräsvirta & Ann-Charlotte Eliasson, 2001. "Non-linear error correction and the UK demand for broad money, 1878-1993," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 277-288.
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    More about this item

    Keywords

    Autometrics; broad money; cointegration; conditional models; dynamic specification; error correction; Friedman and Schwartz; model design; model selection; money demand; nonlinearities; structural breaks; United Kingdom;
    All these keywords.

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • E41 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Demand for Money

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